A scoping review of social media as a platform for multi-level sexual health promotion interventions
Bibliographic record
Abstract
While social media can present unique opportunities for sexual health promotion interventions that target social ecological levels beyond the intrapersonal, health promotion as a discipline has not yet fully realized the potential of these platforms. The following scoping review focuses on the use of social media in the delivery of sexual health interventions targeting the interpersonal, institutional, community, and public policy levels of the social ecological model for change. A total of 398 articles on social media-based sexual health promotion interventions were identified. From this, 67 articles were reviewed in-depth, and 24 met the criteria for inclusion. Of these, four articles described interventions that focused on changing the knowledge, attitudes or behaviour of participants at the intrapersonal level. The remaining 20 articles targeted levels beyond the intrapersonal, with an emphasis on promoting change at broader levels to create environments that support sustained behavioural change. The examples provided by the 24 studies reviewed in this scoping review demonstrate how social media can offer unique health promotion tools for creating social networks and communities to support or deliver intervention activities, as well as for connecting individuals with appropriate and contextually responsive sexual health services. This scoping review provides valuable insights into potential strategies for developing and conducting multi-level social media-based sexual health promotion interventions and identifies areas where outcome and evaluative data are needed to demonstrate impact and potential for scale-up of intervention strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".